Official NVIDIA-authored guidance for NVIDIA cuDF GPU DataFrames, pandas acceleration, dask-cuDF, ETL, joins, groupby, CSV/Parquet I/O, nullable semantics, and multi-GPU DataFrame workloads.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use this skill when the user is doing hands-on host-side DOCA PCC work to load a CUSTOM Programmable Congestion Control algorithm onto a BlueField DPU — creating per-port `doca_pcc` contexts, loading a `dpacc`-compiled `doca_pcc_app` onto the `doca_dev` for the RoCE-bearing port, parameterizing it, walking triple-axis capability discovery (DOCA cap-query + DPA-capable BlueField + firmware custom-PCC slot enabled), or debugging `DOCA_ERROR_*` from `doca_pcc_*`. Trigger even without explicit "DOCA PCC" phrasing — implicit forms include "loading my own congestion control onto a BF port", "DOCA_ERROR_NOT_PERMITTED on algorithm load", "DOCA_ERROR_DRIVER when I attach my custom algorithm", "my custom rate-update isn't affecting RoCE traffic", or "load succeeds but no on-wire change". Refuse and route elsewhere for DPA-side algorithm-body design, the `pcc_counters` CLI, default factory PCC in ConnectX firmware, or setting up the RDMA / RoCE traffic — those belong to other skills.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
doca_pcc + a DPACC-built
doca_pcc_app; do not rewrite the algorithm body here.Follow Loading order below. Open the tasks companion for configure / load / debug. Open the capabilities companion for the triple-axis cap query. Do not open every companion file.
Where to start: This skill assumes DOCA is already installed,
the user's BlueField has a DPA processor that the host can see
through DOCA, the BlueField firmware has the custom-PCC slot
enabled, and the user is doing hands-on custom PCC work from
the host side — i.e. using doca-pcc to load a DPA-side
congestion control algorithm onto the BlueField, attach it to a
port handling RDMA / RoCE traffic, and parameterize it from the
host. Open the tasks companion if the user wants to do
something (configure / build / modify / run / test / debug);
open the capabilities companion when the question is
what can the host-side PCC API express on this version + this
BlueField generation + this firmware. If the user has not
installed DOCA yet, route to
doca-setup first; if the user is
asking how to write the DPA-side congestion-control algorithm
itself (the code that runs on the DPA processor, compiled by
dpacc), that is a different scope — route via
doca-public-knowledge-map
to the public DOCA PCC programming guide and to
doca-dpa for the host-side DPA
lifecycle this skill builds on. If the user only wants to
inspect PCC counters at runtime without writing a custom
algorithm, that is the pcc_counters CLI tool — route via
doca-public-knowledge-map ## DOCA tools;
this skill is for custom algorithms only.
The CLASSES of PCC questions this skill is built to answer, each with one worked example. The agent should treat the class as the load-bearing piece — the worked example is a single instance.
doca_pcc_cap_* against the active
doca_devinfo must agree) in
DOCA_ERROR_NOT_PERMITTED
even though I have doca_dev access?" — worked example:
"the BlueField firmware in this host has the custom-PCC slot
disabled". Answered by the permission matrix in
doca-pcc library the right tool for what I want,
or do I want the default firmware PCC or the
pcc_counters CLI?" — worked example: "I just want to
read PCC counters without touching the algorithm". Answered
by the path-selection rule in
doca-public-knowledge-map ## DOCA tools
for the counter tool.doca-version and adds the
PCC-specific DOCA must match DPACC overlay inherited from
doca-dpa.DOCA_ERROR_* from a doca_pcc_* call mean
and which layer caused it?" — worked example:
"DOCA_ERROR_DRIVER on the host-side algorithm-load call —
is it DOCA, the firmware-side custom-PCC slot, or the DPACC-
produced image?". Answered by the PCC overlay on the
cross-library taxonomy in
doca-debug.This skill serves external developers building applications
that consume the DOCA PCC library from the host side — i.e.,
users whose code calls doca_pcc_* from host C / C++ to stand
up the per-PCC-instance context, load a DPA-side PCC algorithm
image that dpacc produced from their DPA-side source, attach
it to the BlueField port that carries the RDMA / RoCE traffic
the algorithm is meant to control, parameterize the algorithm,
start the context, and observe runtime reports back from the
algorithm. It is not for NVIDIA developers contributing to
DOCA PCC itself, nor is it the place to learn how to write
the DPA-side congestion-control algorithm itself (that path
goes through the public DOCA PCC programming guide and the
companion DOCA DPA / DPACC guides via
doca-public-knowledge-map).
Language scope. DOCA PCC ships as a host-side C library
with pkg-config module name doca-pcc. The host-side API is
C; the DPA-side congestion-control algorithm is a separate
translation unit written in the language the DPACC compiler
accepts and compiled by dpacc into a binary that the host
packages into the executable as the PCC algorithm image. The
shipped samples under /opt/mellanox/doca/samples/doca_pcc/
are written in C plus DPA-side source (NVIDIA's choice).
Other-language consumers are limited in practice — the
DPA-side algorithm has no FFI escape hatch because it must be
a translation unit dpacc accepts — but a Rust / Go / Python
host-side wrapper that drives doca_pcc_* setup and loads a
PCC algorithm image built separately is still useful, and the
skill keeps the lifecycle, capability-discovery,
env-precondition, and error-taxonomy guidance language-neutral.
Load this skill when the user is doing hands-on DOCA PCC work
from the host side for a custom congestion control
algorithm, in any host language plus a DPA-side translation
unit built by dpacc. Concretely:
doca_pcc against a doca_dev that maps to
the BlueField port carrying the RDMA / RoCE traffic to be
controlled.doca_pcc_app) that dpacc
produced from the user's DPA-side congestion-control algorithm
source, into the doca_pcc context.doca_pcc Core
context so the algorithm begins affecting RDMA / RoCE
traffic on the attached port.doca_devinfo via the doca_pcc_cap_* family — BlueField
generations and firmware revisions differ in whether they
permit a custom PCC algorithm.DOCA_ERROR_* returned from a doca_pcc_* call
— in particular disambiguating firmware-level custom-PCC
slot disabled from device does not support custom PCC at
all from algorithm image incompatible with this device
from standard doca_dev access denied.dpacc — the env-precondition and capability-discovery rules
in this skill still apply.Do not load this skill for general DOCA orientation, install
of DOCA or the DPACC compiler, the DPA-side programming model
itself (how to write the congestion-control algorithm body that
runs on the DPA), questions about the default factory PCC
algorithm shipped in ConnectX firmware (no host-side doca-pcc
code needed — that path is firmware-only configuration), or
questions about the pcc_counters diagnostic CLI (route via
doca-public-knowledge-map ## DOCA tools).
For all of those, route through
doca-public-knowledge-map
to the matching upstream guide.
This is a thin loader. The body keeps only the orientation needed to pick the right next file. The substantive PCC-specific material lives in two companion files:
doca_pcc context, the loaded doca_pcc_app
algorithm image produced by dpacc, the attach-to-port
semantics that bind the algorithm to the RDMA / RoCE traffic
it will control, the capability-query surface
(doca_pcc_cap_*), the PCC error taxonomy mapped onto the
cross-library DOCA_ERROR_* set, the observability surface
(host-side reports plus the public PCC counter tool reachable
via doca-public-knowledge-map), and the safety policy that
gates env preconditions (DPA-capable BlueField, firmware-level
custom-PCC slot enabled, matched DOCA + DPACC versions,
algorithm image and host-side expectations agree).configure, build, modify, run, test,
debug. Plus a Deferred task verbs block that points
out-of-scope questions at the right next skill.The skill assumes a host where DOCA is already installed at
the standard location, a BlueField with a DPA processor is
physically present and visible to the host, the BlueField
firmware has the custom-PCC slot enabled, the DPACC compiler
is installed at a version matched to the DOCA install per the
DOCA Compatibility Policy, and the user already knows how
(at least at a sketch level) to write the DPA-side PCC
algorithm that dpacc will compile. It does not cover
installing DOCA, installing the DPACC compiler, or flipping
firmware-level configuration — those paths go through
doca-setup.
This skill is agent guidance, not a samples or templates bundle. To keep the boundary clean, it deliberately does not contain — and pull requests should not add:
/opt/mellanox/doca/samples/doca_pcc/. The agent's job is to
route the user to those files and prescribe a minimum-diff
modification on them via the universal modify-a-sample
workflow in
doca-programming-guide,
layered with the PCC-specific overrides in
meson.build,
CMakeLists.txt, …) parked inside the skill. The agent
constructs the build manifest in the user's project
directory against the user's installed DOCA + DPACC
compiler, where pkg-config --modversion doca-pcc and the
installed dpacc are the two sources of truth.samples/, bindings/, or reference/ subtree of any
kind. A mock or incomplete artifact in this skill's tree,
even one labeled "reference", is misleading: users will read
it as buildable.pcc_counters tool surface. That CLI is a separate
artifact (the pcc_counters.sh script under
tools/pcc_counters/) with its own page; routing lives in
doca-public-knowledge-map ## DOCA tools.
Conflating it with the library is the most common PCC
first-app design error.doca_pcc per-instance context, the loaded doca_pcc_app
algorithm image, the attach-to-port semantics, the
triple-axis precondition rule, the env-precondition policy,
the error taxonomy, the observability surface, and the
safety policy, see the capabilities companion.Both companion files cross-link to each other,
doca-version for the canonical
DOCA version-handling rules (with the PCC overlay that DOCA
must match the DPACC compiler), and
doca-public-knowledge-map
whenever the right answer is "look it up in the public DOCA
PCC programming guide, the public DPA / DPACC guides, the
pcc_counters tool guide, or in the on-disk install
layout" rather than "PCC host-side-specific guidance".
doca-public-knowledge-map —
the routing table for every public DOCA documentation
source and the on-disk layout of an installed DOCA package.
The PCC public guide is at
https://docs.nvidia.com/doca/sdk/DOCA-PCC/index.html; the
pcc_counters diagnostic CLI lives under the DOCA Tools
umbrella as a companion surface rather than a redefined
artifact here.doca-dpa — the host-side DPA
control library that PCC depends on conceptually: the
custom PCC algorithm is DPA-side code, compiled by the
DPACC compiler, and the host-side doca-pcc Core lifecycle
follows the same shape as the doca-dpa Core lifecycle. The
agent loads doca-dpa alongside this skill when the user
has DPA-level questions (kernel-launch model, DPA-side
libraries) that PCC is layered on top of.doca-rdma — the library whose
traffic the custom PCC algorithm is controlling. The custom
PCC algorithm affects RDMA / RoCE flows on the attached
BlueField port; if the user has not yet set up RDMA / RoCE
traffic on that port, there is nothing for the algorithm to
act on, and doca-rdma is the skill that brings that
traffic up.doca-setup — env preparation,
install verification, DPACC compiler install / verification,
BlueField firmware configuration (including the custom-PCC
slot enable), and the I have no install yet path with the
public NGC DOCA container. This skill assumes its
preconditions are satisfied AND that DPACC is installed at a
version that matches DOCA AND that the firmware-level
custom-PCC slot is enabled.doca-version — canonical
DOCA version-handling rules. This skill's ## Version compatibility cross-links the four-way match rule and adds
the PCC-specific DOCA-and-DPACC must match overlay per the
DOCA Compatibility Policy (inherited from
doca-dpa).doca-structured-tools-contract —
the bundle's structured-tools precedence rule (detect /
prefer / fall back / report). The Command appendix in
the tasks companion honors this contract.doca-programming-guide —
general DOCA programming patterns shared by every library:
the canonical pkg-config + meson build pattern, the
universal modify-a-shipped-sample first-app workflow, the
universal Core-context lifecycle, the cross-library
DOCA_ERROR_* taxonomy, and the program-side debug order.
This skill layers PCC specifics on top.doca-debug — the cross-cutting
debug ladder (install / version / build / link / runtime /
program / driver). PCC-specific debug (custom-PCC slot not
enabled in firmware, DPACC + DOCA version skew, algorithm
image rejected as incompatible with the device, a loaded
algorithm producing no on-wire change because
doca_pcc_start() was never called or the attached port
carries no RoCE traffic) overlays on top of that ladder."It loads but nothing changes on the wire" is a host-side question. A successful load is not a live algorithm:
doca_pcc_start()is the moment it goes live on the port, and PCC only modulates RoCE traffic that already exists on thedoca_devthedoca_pccwas created against. Settle both here and do not audit the DPA-side algorithm body: that isdoca-dpa's surface, and reports firing already proves the body runs — what is unproven is that it is bound and live. Ordered checks indebug.
아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.
아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.
Official NVIDIA-authored guidance for NVIDIA cuDF GPU DataFrames, pandas acceleration, dask-cuDF, ETL, joins, groupby, CSV/Parquet I/O, nullable semantics, and multi-GPU DataFrame workloads.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Customize NVIDIA Nemotron Voice Agent's Generic Pipecat example for healthcare appointment, five-field patient intake, or custom tool-calling workflows without a separate backend.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Calibrate a new dataset from live RTSP camera streams via the AutoMagicCalib REST API. Use when the user provides RTSP URLs or asks to calibrate live cameras; VIOS records clips, AMC ingests them, then runs calibration.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Run end-to-end calibration on the shipped sample dataset (sdg_08_2_sample_data_010926.zip) against a running AMC microservice. Use when user says 'test sample dataset', 'run sample calibration', 'verify AMC install', or 'launch and test'.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Calibrates pre-recorded `cam_*.mp4` datasets through the AutoMagicCalib REST API. Use for user-supplied local MP4s; route live RTSP streams to `amc-run-rtsp-calibration`.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Launch AutoMagicCalib microservice and web UI from NGC release images via Docker Compose. Use when user says 'deploy auto calibration', 'launch auto calibration', 'launch AMC', 'start MS+UI', or 'set up auto-magic-calib'. Requires NGC API key.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.